Kudo Masataka, Sasaki Sho, Takada Toshihiko, Fujii Kotaro, Yagi Yu, Yano Tetsuhiro, Sada Ken-Ei, Fukuhara Shunichi, Suganuma Narufumi
Department of General Internal Medicine Iizuka Hospital Fukuoka Japan.
Department of Clinical Epidemiology Kochi Medical School Nankoku Japan.
J Gen Fam Med. 2025 Feb 5;26(3):238-245. doi: 10.1002/jgf2.764. eCollection 2025 May.
Quick Sequential Organ Failure Assessment (qSOFA) is a simple and easy tool for identifying patients with suspected infection, who are at a high risk of poor outcome. However, its predictive performance is still insufficient. The Eastern Cooperative Oncology Group Performance Status (ECOG-PS) score, a tool to evaluate physical function, has been recently reported to be useful in predicting the prognosis of patients with pneumonia. We aimed to evaluate the added value of ECOG-PS to qSOFA in predicting 30-day mortality in older patients admitted with suspected infections.
Between 2018 and 2019, we prospectively collected data from adults aged 65 years or older, admitted with suspected infection at two acute care hospitals. Predictive performance was compared between two logistic regression models: one using qSOFA score alone (qSOFA model) and the other in which ECOG-PS was added to qSOFA (extended model).
Of the 1536 enrolled patients, 135 (8.8%) died within 30 days. The area under the curve of the extended model was significantly higher than that of the qSOFA model (0.67 vs. 0.64, = 0.008). When the risk groups were categorized as follows: low (<5%), intermediate (5%-10%), and high (≥10%), 5.0% of those who died and 2.1% of those who survived were correctly reclassified by the extended model with an overall categorized net reclassification improvement of 0.03 (95% confidence interval: -0.06 to 0.30).
Adding the ECOG-PS score could improve the performance of qSOFA in predicting mortality in older patients admitted with suspected infection.
快速序贯器官功能衰竭评估(qSOFA)是一种简单易用的工具,用于识别疑似感染且预后不良风险较高的患者。然而,其预测性能仍显不足。东部肿瘤协作组体能状态(ECOG-PS)评分是一种评估身体功能的工具,最近有报道称其在预测肺炎患者的预后方面很有用。我们旨在评估ECOG-PS对qSOFA在预测疑似感染入院老年患者30天死亡率方面的附加价值。
在2018年至2019年期间,我们前瞻性地收集了两家急症医院收治的65岁及以上疑似感染成年患者的数据。比较了两个逻辑回归模型的预测性能:一个仅使用qSOFA评分(qSOFA模型),另一个是在qSOFA中加入ECOG-PS(扩展模型)。
在1536名登记患者中,135名(8.8%)在30天内死亡。扩展模型的曲线下面积显著高于qSOFA模型(0.67对0.64,P = 0.008)。当将风险组分类如下:低(<5%)、中(5%-10%)和高(≥10%)时,扩展模型正确重新分类了5.0%的死亡患者和2.1%的存活患者,总体分类净重新分类改善为0.03(95%置信区间:-0.06至0.30)。
加入ECOG-PS评分可提高qSOFA在预测疑似感染入院老年患者死亡率方面的性能。